Understanding how cells develop and perform their physiological roles in complex tissues will require understanding the small molecule metabolites that are used as building blocks for biosynthesis, as signaling molecules to regulate the activity of the cell, or used to signal between cells. Visualizing these metabolites in intact tissue that preserves the architecture of the tissue will be required to get a better understanding of how the tissue works or develops. The problem is compounded by the need to survey 10,000s of metabolites, or the entire metabolome, in unbiased approaches to discover underlying mechanisms of the tissue. Mass spectrometry (MS) methods to visualize entire metabolomes in tissue sections, Metabolomic In Situ Imaging (MISI), have been developed, but remain poorly utilized. This is largely due to the inability to relate specific cell types to metabolite profilesin the MISI image. We propose to develop methods that will allow unambiguous identification of distinct cell types. We will identify or generate labels that uniquely mark different cells. These labels will be ionized and taken into the MS together with the sampled metabolome, thus coupling cell type identifiers to each metabolome profile in the section. We will explore three approaches to identifying cell type specific labeling for MISI (a) use of endogenous metabolites specific to cell types, (b) detection of cell-type transgenic expression of GFP, and (c) development of cell type-specific antibiotic conversion by transgenically expressed antibiotic resistance genes. We will use cell type-specific labeling to explore different metabolisms of growing or quiescent cells in the regenerating zebrafish fin. Development of these methods will open the doors on our ability to see how cells of a lineage behave differently at different positions within an organ, or how different cell types next to each other coordinate their functions. Such analysis will push forward our understanding of how animals develop properly, or how cancer cells do it wrong.